危重症患者失禁相关性皮炎风险列线图预测模型的建立与验证

Establishment and validation of nomogram prediction model for incontinence-associated dermatitis risk in critically ill patients

目的:构建危重症患者失禁相关性皮炎(incontinence-associated dermatitis,IAD)风险预测的列线图模型,及时评估IAD的发生风险。方法:选取某三级甲等中西医结合医院ICU住院患者359例,按IAD发生与否分为未发生组(n=257)和发生组(n=102)后进行单因素分析,再进行多因素Logistic回归分析,利用R软件建立风险预测的列线图模型并进行内部验证。结果:本研究最终纳入发热(P=0.001,OR=3.252)、双便失禁(P=0.001,OR=3.510)、每日大便次数(P<0.001,OR=2.987)、PAT评分(P=0.002,OR=1.268)与中医辨证施护(P<0.001,OR=4.540)5个影响因素建立风险预测的列线图模型,模型的C-index值为88.40%,校准度显示预测概率与IAD实际发生概率趋于一致,DCA决策曲线显示该列线图的临床有用性良好。结论:本模型预测效果良好,并结合了中医辨证思想,适用于中西医临床实际,可为ICU医护人员早期及时对高危患者采取预防性护理干预提供参考。

Objective:To timely assess the risk of incontinence-associated dermatitis(IAD)by constructing a nomogram-predicting model for the risk prediction of IAD in critically ill patients.Method:A total of 359 ICU patients in a tertiary hospital of integrated traditional Chinese and Western medicine were selected,and divided into the nonoccurrence group(n=257)and occurrence group(n=102)according to the IAD happens or not.Univariate and multivariable logistic regression analysis were used to analysis the risk factors for IAD.A nomogram-predicting model was build based on the logistic regression model by R software.Results:Five risk factors,including fever(P=0.001,OR=3.252),the double incontinence(P=0.001,OR=3.510),daily stool frequency(P<0.001,OR=2.987),PAT score(P=0.002,OR=1.268),and TCM syndrome differentiation nursing(P<0.001,OR=4.540),were taken to construct a nomogram-predicting model.The model displayed good discrimination with a C-index of 0.884 and good calibration,and the predicting probability of the model was consistent with the probability of occurrence of IAD.Decision curve analysis showed that the model was clinically useful.Conclusion:This nomogram-predicting model has satisfactory prediction by combining with the theory of TCM syndrome differentiation.The risk prediction can be completed at the beginning of ICU stay,which can provide reference for preventative treatment and nursing measures for high-risk patients.